1. Field of the Invention
This invention relates to an image processing method and apparatus for carrying out image processing on an image of a predetermined frequency band in an original image.
2. Description of the Prior Art
Techniques for obtaining an image signal, which represents an image, carrying out appropriate image processing on the image signal, and then reproducing a visible image by use of the processed image signal have heretofore been known in various fields. For example, in Japanese Unexamined Patent Publication No. 55(1980)-163772, the applicant proposed a method for carrying out frequency emphasis processing, such as unsharp mask processing, on an image signal, such that a visible radiation image may be obtained, which has good image quality and can serve as an effective tool in, particularly, the efficient and accurate diagnosis of an illness. With the frequency processing, an unsharp mask signal is subtracted from an image signal representing an original image, the resulting difference value is multiplied by an emphasis coefficient, and the thus obtained product is added to the image signal. In this manner, predetermined frequency components in the image are emphasized.
A different method for carrying out frequency processing on an image signal has also been proposed. With the proposed frequency processing method, an image is transformed into multi-resolution images by a Fourier transform, a wavelet transform, a sub-band transform, or the like, and the image signal representing the image is thereby decomposed into signals falling within a plurality of different frequency bands. Thereafter, of the decomposed signals, a signal falling within a desired frequency band is subjected to predetermined image processing, such as emphasis.
Further, recently, in the field of image processing, a novel technique for transforming an image into a multi-resolution space, which is referred to as the Laplacian pyramid technique, has been proposed in, for example, Japanese Unexamined Patent Publication No. 6(1994)-301766. With the proposed Laplacian pyramid technique, mask processing is carried out on the original image by using a mask having characteristics such that it may be approximately represented by a Gaussian function. A sub-sampling operation is then carried out on the resulting image in order to thin out the number of the picture elements to one half along each of two-dimensional directions of the array of the picture elements in the image, and an unsharp image having a size of one-fourth of the size of the original image is thereby obtained. Thereafter, a picture element having a value of 0 is inserted into each of the points on the unsharp image, which were eliminated during the sampling operation, and the image size is thereby restored to the original size. Mask processing is then carried on the thus obtained image by using the aforesaid mask, and an unsharp image is thereby obtained. The thus obtained unsharp image is subtracted from the original image, and a detail image of a predetermined frequency band of the original image is thereby obtained. This processing is iterated with respect to the obtained unsharp image, and N number of unsharp images having sizes of 1/2.sup.2N of the size of the original image are thereby formed. As described above, the sampling operation is carried out on the image, which has been obtained from the mask processing with the mask having characteristics such that it may be approximately represented by the Gaussian function. Therefore, though the Gaussian filter is used actually, the same processed image as that obtained when a Laplacian filter is used is obtained. Also, in this manner, the images of low frequency bands, which have the sizes of 1/2.sup.2N of the size of the original image are successively obtained from the image of the original image size. Therefore, the group of the images obtained as a result of the processing is referred to as the Laplacian pyramid.
The Laplacian pyramid technique is described in detail in, for example, "Fast Filter Transforms for Image Processing" by Burt P. J., Computer Graphics and Image Processing, Vol. 16, pp. 20-51, 1981; "Fast Computation of the Difference of Low.cndot.Pass Transform" by Growley J. L., Stern R. M., IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 6, No. 2, March 1984; "A Theory for Multiresolution Signal Decomposition; The Wavelet Representation" by Mallat S. G., IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 11, No. 7, July 1989; "Image Compression by Gabor Expansion" by Ebrahimi T., Kunt M., Optical Engineering, Vol. 30, No. 7, pp. 873-880, July 1991; and "Multiscale Image Contrast Amplification" by Pieter Vuylsteke, Emile Schoeters, SPIE, Vol. 2167, Image Processing (1994), pp. 551-560.
Japanese Unexamined Patent Publication No. 6(1994)-301766 mentioned above discloses a method, wherein processing for emphasizing image values is carried out on the images of all of the frequency bands in the Laplacian pyramid, which images have been obtained in the manner described above, and the image of each frequency band, which has been obtained from the emphasis processing, is then subjected to an inverse transform, and a processed image is thereby obtained. In the disclosed method, the image emphasis is carried out on the image signal of each frequency band by using the formula shown below. EQU y=-m.times.(x/m).sup.p (x&lt;0) EQU y=m.times.(-x/m).sup.p (x.gtoreq.0)
wherein x represents the picture element value of each picture element in the image, y represents the picture element value of each picture element in the image obtained from the emphasis processing, and m represents the range of values which the picture elements can take (for example, m=1,023 in cases where the range of values, which the picture elements can take, is 10 bits). Specifically, as the value of p becomes smaller, the degree of emphasis becomes higher. As the value of p becomes larger, the degree of emphasis becomes lower. The image emphasis is carried out with such a degree of emphasis. In the image obtained from such processing, the image has been emphasized in each frequency band. Therefore, an image is obtained such that unsharp mask processing might have been carried out substantially with masks having a plurality of sizes in the aforesaid unsharp mask processing.
However, in the method disclosed in Japanese Unexamined Patent Publication No. 6(1994)-301766 mentioned above, when the emphasis processing is carried out on the image of a certain frequency band, unnecessary components, such as noise, are emphasized together with the image components, such as contours of the object, which it is necessary to emphasize. Therefore, as a result of the processing, an image is obtained in which the components, such as contours of the object, and noise have been emphasized. Accordingly, the image obtained from the image processing becomes difficult to view due to much noise.
Also, in the method disclosed in Japanese Unexamined Patent Publication No. 6(1994)-301766 mentioned above, the emphasis processing is carried out with the same degree of emphasis for all of different regions in the image of each frequency band. For example, in cases where the image to be emphasized is a radiation image of the chest of a human body, an image portion having a comparatively high density, such as the lung field region, is the one which was recorded with a large amount of radiation and contains little quantum noise. However, an image portion having a comparatively low density, such as the mediastinum region, is the one which was recorded with a small amount of radiation and contains much quantum noise. Therefore, if the emphasis processing is carried out on the radiation image of the chest by using the method disclosed in Japanese Unexamined Patent Publication No. 6(1994)-301766, noise in the mediastinum region will become perceptible in the image, which is obtained from the emphasis processing, and the image will become difficult to view.